Dr Hans Ren

Tutor in Computer Science

Computer Science

hanchi.ren@swansea.ac.uk

Admin - 015
Ground Floor
Computational Foundry
Bay Campus

Research Links

ResearchGate

Google Scholar

About

Dr Hanchi Ren is a Tutor and a member of the Computer Vision and Machine Learning group (http://csvision.swan.ac.uk) in the Department of Computer Science, Swansea University, where he completed both his PhD (2023) and MSc (2016) degrees.

With the successes of deep learning in many computational cognitive tasks, AI has been becoming the core of digital infrastructure. Majority of Dr Hanchi Ren’s work is closely related to applied machine learning to diverse industrial and consumable products. Therefore, his research and teaching interest is mainly focus on the fundamental advancement of theoretical machine learning and its applications in computer vision, big data and privacy preservation.

Areas Of Expertise

Computer Vision
Privacy Preservation
Machine Learning
Deep Learning

Publications

Research Highlights

Hu, F., Ren, H., Hu, C., Deng, J., & Xie, X. (2024). An Element-Wise Weights Aggregation Method for Federated Learning. In 2023 IEEE International Conference on Data Mining Workshops (ICDMW)IEEE.
https://doi.org/10.1109/icdmw60847.2023.00031, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66909
Watson, M., Ren, H., Arvin, F., & Hu, J. (2024). Predator-Prey Q-Learning Based Collaborative Coverage Path Planning for Swarm Robotics. In 2024 Annual Conference Towards Autonomous Robotic Systems (TAROS)Springer.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66908
https://link.springer.com/conference/taros
Li, Y., Ren, H., Deng, J., Ma, X., & Xie, X. (2024). Centersam: Fully Automatic Prompt for Dense Nucleus Segmentation. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI) (pp. 1-5). IEEE.
https://doi.org/10.1109/isbi56570.2024.10635872, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66747
Xie, X., Hu, C., Ren, H., & Deng, J. (2024). A survey on vulnerability of federated learning: A learning algorithm perspective. Neurocomputing, 573, 127225
https://doi.org/10.1016/j.neucom.2023.127225, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65451
Ren, H., Deng, J., Xie, X., Ma, X., & Wang, Y. (2024). FedBoosting: Federated learning with gradient protected boosting for text recognition. Neurocomputing, 569
https://doi.org/10.1016/j.neucom.2023.127126, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65267

All Research

Journal Articles

Ren, H., Wang, Y., & Ma, H. (2024). Deep Prediction Network Based on Covariance Intersection Fusion for Sensor Data. IECE Transactions on Intelligent Systematics, 1(1), 10-18.
https://doi.org/10.62762/tis.2024.136898, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67603
Xie, X., Hu, C., Ren, H., & Deng, J. (2024). A survey on vulnerability of federated learning: A learning algorithm perspective. Neurocomputing, 573, 127225
https://doi.org/10.1016/j.neucom.2023.127225, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65451
Ren, H., Deng, J., Xie, X., Ma, X., & Wang, Y. (2024). FedBoosting: Federated learning with gradient protected boosting for text recognition. Neurocomputing, 569
https://doi.org/10.1016/j.neucom.2023.127126, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65267
Ren, H., Deng, J., & Xie, X. (2022). GRNN: Generative Regression Neural Network - A Data Leakage Attack for Federated Learning. ACM Transactions on Intelligent Systems and Technology, 13(4)
https://doi.org/10.1145/3510032, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59093
Ren, H., Hu, F., Myint, S., Hou, K., Zhang, X., Zuo, M., Zhang, C., Zhang, Q., & Li, H. (2021). A Real-Time and Long-Term Face Tracking Method Using Convolutional Neural Network and Optical Flow in IoT-Based Multimedia Communication Systems. Wireless Communications and Mobile Computing, 2021, 1-15.
https://doi.org/10.1155/2021/6711561, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58621

Conference Contributions

Hu, F., Ren, H., Hu, C., Li, Y., Deng, J., & Xie, X. (2024). Gradients Stand-in for Defending Deep Leakage in Federated Learning. In International Conference on Computing in Natural Sciences, Biomedicine and Engineering
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66608
Li, Y., Ren, H., Deng, J., Ma, X., & Xie, X. (2024). Centersam: Fully Automatic Prompt for Dense Nucleus Segmentation. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI) (pp. 1-5). IEEE.
https://doi.org/10.1109/isbi56570.2024.10635872, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66747
Watson, M., Ren, H., Arvin, F., & Hu, J. (2024). Predator-Prey Q-Learning Based Collaborative Coverage Path Planning for Swarm Robotics. In 2024 Annual Conference Towards Autonomous Robotic Systems (TAROS)Springer.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66908
https://link.springer.com/conference/taros
Hu, F., Ren, H., Hu, C., Deng, J., & Xie, X. (2024). An Element-Wise Weights Aggregation Method for Federated Learning. In 2023 IEEE International Conference on Data Mining Workshops (ICDMW)IEEE.
https://doi.org/10.1109/icdmw60847.2023.00031, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa66909